1. Field of the Invention
This invention relates to a device whereby noise can be extracted from short duration periodic signals succeeding each other at random intervals. The device can be applied to fringe laser velocimetry in order to measure the instantaneous rate of flow of gases or liquids, using particles carried by the fluid as a tracer; these particles have a dimension of around 1 micron and are most often introduced artificially.
More generally speaking the invention concerns a system of processing signals whereby it is possible to detect and frequency analyze, in real time, short duration periodic signals drowned in noise and having unforeseeable occurrence times.
To measure the flow rate of a fluid by fringe laser velocimetry, a network of interference fringes is formed by intersecting two laser beams at a given point in the flow; the point is referred to as "test volume". A particle traversing the test volume encounters successively clear and obscure parts of the fringes and diffuses light in all directions.
A photomultiplier having a field of view directed at the test volume therefore is responsive to light flux modulated sinusoidally at a frequency: EQU f=v/i (1)
in which v is the speed of the particles and i the pitch between fringes.
This modulated signal has a Gaussian envelope representing the intensity distribution of the luminous flux in the test volume. After high-pass filtering, the signal derived by the photomultiplier can be expressed as: EQU s(t)=a.multidot.cos .omega.t.multidot.exp (-t.sup.2 /2.sigma..sup.2) (2)
where
.omega.=2.sigma./v and PA1 .sigma.: standard deviation of the Gaussian envelope. PA1 b(t) is white noise, .omega. is angular frequency of the useful signal, and exp (-t.sup.2 /2.sigma..sup.2) is the Gaussian envelope or error function of the useful signal.
A more or less intensive noise b(t) is generally superposed on the signal s(t) according to the position of the test volume in relation to walls guiding the flow, and according to the way in which the photomultiplier receives the luminous flux (prior or back diffusion, . . . ).
2. Description of the Prior Art
There are two main classes of speed measuring devices which produce substantially different results:
1. Global testing, over a large number of particles, to provide a statistical estimate of average speed and its standard deviation characterizing turbulence;
2. Testing instantaneous speed of each particle to provide corresponding dating. The second class obviously has a higher performance because it provides access to other values (higher order moments, turbulence spectrum, etc., . . . ), as well as mean speed and its standard deviation. Moreover only these means provide access to the instantaneous speed vector in a bi-dimensional or tri-dimensional mode. The system of the invention is in this latter category.
In systems for globally analyzing a sample of N particles, the signal derived by the photomultiplier can be recognized by responding with analog circuitry to different frequency bands. In the spectrum thus obtained from the photodetector output signal, the white noise results in a continuous signal whereas the useful signal results in a more or less wide peak according to the flow turbulence energy. This method, while being relatively immune to noise, is not very fast or accurate.
A digital spectral analysis can also be performed either via a band-pass scanning filter, or via plural parallel filters. The system is more accurate but is slow (if only one filter is used), or costly (in the event of plural parallel filters).
A real time digital correlator can be used to extract, from the "useful signal plus white noise" sum, a periodic useful component. Because white noise only affects the first coefficient of the signal autocorrelation function, it is simply necessary to acquire the C.sub.n .noteq.0 correlation to extract the signal from the noise.
Average speed and turbulence intensity can be deduced directly from the autocorrelation function, but it is easier to first form the Fourier transform and determine these values from the power spectrum. The commercial, MALVERN correlator uses this principle, digitizing the signal with only one bit.
To measure instantaneous speed it is necessary with previously used devices to detect the occurrence time of a particle passing through the test volume. The different systems in the second category can be therefore singled out, firstly, by the way in which this detection is made and secondly, by estimating the frequency of the useful signal, hence the speed of the particles.
The method most currently used in laser velocimetry of this type is the so-called "counting" method. The useful signal is detected by comparing its amplitude to a threshold; its frequency is measured by counting the number of pulses derived from a high speed clock over a certain number of periods of the frequency to be measured.
This method is relatively accurate (although limited by the maximum frequency of the counting clock: 500 MHz) but it is ineffective when noise level rises. In fact, signal zero crossings are not significant.
A prior art spectral analysis method is the subject of Dieter Pallek's article on the DFVLR "Fast Digital Data Acquisition and Analysis of LDA Signals by Means of a Transient Recorder and an Array Processor" published in the ICIASF'85 Record. When the amplitude of the signal exceeds a certain threshold, a portion of the signal is acquired, in a pre-activated mode, having a duration corresponding approximately to the time required for the particle to cross the test volume. Then a Fourier transform of the signal is made and its power spectrum calculated via a parallel "array processor" computer.
This method is relatively immune to noise but requires the presence of the useful signal to produce an increase of the global level detectable via a threshold. This method is therefore difficult to apply when the signal/noise ratio is relatively low. Moreover the system is not very fast and is relatively costly.
Another method of spectral analysis is described in the article "Frequency Domain Laser Velocimeter Signal Processor," James F. Meyer, published in the Proceedings of the "Third International Symposium on Applications of Laser Anemometry to Fluid Mechanics." This technique has a high performance because it detects an energy threshold, instead of detecting a signal amplitude threshold that is sensitive to the noise. The system calculates the energy of the signal continuously over a constant time window T. If this energy exceeds a certain threshold, it is assumed that a particle passing the window has been detected. The corresponding signal is stored, then applied to an input of plural, parallel band-pass filters to determine frequency. To calculate energy, the signal is digitized as one bit; for the filtering it is digitized as two bits.
As the number of band-pass filters is not very high, one acts iteratively on the sampling frequency to obtain a maximum energy from the central filter. A certain number of particles of the same speed are therefore required to converge.
The MEYERS method described above has two drawbacks:
a. While the "threshold" applied to the energy contained in the time window T of the signal is better than that applied to the amplitude, it incorrectly assumes that the noise energy in the window is always relatively constant. Moreover, in the presence of a strong noise component, the noise difference between the energy and the "noise plus signal" can be slight which makes "thresholding" delicate;
b. The system requires a learning period to adapt the sampling rate to the frequency of the signal to adjust the filter response curve to this same frequency.
As a result the measurement is not strictly instantaneous.